Techniques

A Clockwork RNN ICML 2014 Adaptive Sampling for Large Scale Boosting JMLR 2014 Attentional Neural Network: Feature Selection Using Cognitive Feedback NeurIPS 2014 Deep Networks with Internal Selective Attention through Feedback Connections NeurIPS 2014 Dropout: A Simple Way to Prevent Neural Networks from Overfitting JMLR 2014 How transferable are features in deep neural networks? NeurIPS 2014 Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation NeurIPS 2014 Learning by Stretching Deep Networks ICML 2014 Learning Generative Models with Visual Attention NeurIPS 2014 Pre-training of Recurrent Neural Networks via Linear Autoencoders NeurIPS 2014 Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation CVPR 2014 Towards End-To-End Speech Recognition with Recurrent Neural Networks ICML 2014 Adaptive dropout for training deep neural networks NeurIPS 2013 Dropout Training as Adaptive Regularization NeurIPS 2013 Fast dropout training ICML 2013 Gated Autoencoders with Tied Input Weights ICML 2013 Image Matting with Local and Nonlocal Smooth Priors CVPR 2013 Predicting Parameters in Deep Learning NeurIPS 2013 Regularization of Neural Networks using DropConnect ICML 2013 Wavelets on Graphs via Deep Learning NeurIPS 2013 Zero-Shot Learning Through Cross-Modal Transfer NeurIPS 2013 A Better Way to Pretrain Deep Boltzmann Machines NeurIPS 2012 Deep Learning Made Easier by Linear Transformations in Perceptrons AISTATS 2012 Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform NeurIPS 2010 Kernel Descriptors for Visual Recognition NeurIPS 2010